Managing in the Era of Data, Analytics, and Artificial Intelligence

This program gives a comprehensive overview of practical data analytics, as well as a hands-on look at the mechanics behind Artificial Intelligence. Learn to navigate new technologies, think critically about data, and create real value for your organization.

Business Analytics.jpg

Program Overview

Increasingly crowded by data, executives are faced with a clear but complex challenge: seeing through the noise. Volumes of data, collected constantly, hold key insights for business leaders but what are the right questions to ask? How do you interface with data scientists, marketers, and product designers as they interpret and communicate raw information back from the market?

Leading a team who work with data requires some know-how. More importantly, senior leaders need to understand how to organize around data. Structuring teams, hiring for critical capabilities, encouraging an aligned culture — all influence how effectively your organization will turn data insights into action.

Managing with Data gives a comprehensive overview of practical data analytics, as well as a hands-on look at the mechanics behind Artificial Intelligence. Participants take a guided look at successful data-driven organizations, drawing best practices on team structure, emerging technologies, digital transformation, and more. By the end of an intensive two-day program, you'll develop a clear strategy for both creating and communicating value using data.

Come away ready to organize your team, align your culture, and lead your organization through data-driven change.

 

What You Learn

Data Ownership & Leading with Analytics 

  1. Understanding how Analytics works and what it can do for you;
  2. Using the Analytical lens to gain new business insight;
  3. Taking ownership of your data and making data-driven decisions;
  4. Managerial Intuition through Technical Insight.

Understanding Uncertainty 

  1. Distinguishing between process and outcome;
  2. Quantifying trade-offs between rewards and risks;
  3. Simulation-based forecasting and decision making.

Generating Insights & Communicating with Data

  1. Understanding data generated reports and calling “bullshit!”
  2. Persuasive data visualizations and presentation;
  3. Translating data-lingo to business fundamentals;
  4. Converting the skeptic   

Leadership and Management Aspects of Analytics 

  1. Assembling and Leading the Analytics team;
  2. Promoting data-driven culture and dispelling 'dataphobia';
  3. Avoiding the Pitfalls of Analytical Bias and Anchoring; 
  4. Learning from real-world Analytics projects;
  5. Understanding and using new technologies in Analytics to generate value.

Follow-up Webinar 

  1. Tracking the progress of Analytics in your organization; 
  2. Sharing best practices & pitfalls in implementing Analytics;
  3. Exploring the next step – Prescriptive Analytics.

How You Learn

The program combines case-studies and experiential approaches to learning. Participants learn from faculty and one another by working in groups to solve open-ended problems. Check your ideas against Ivey research expertise as you go, focusing dozens of trial-and-error cycles into a single risk-free learning experience.

Learn with other leaders from across sector and industries, share ideas, and reflect on the potential within your own organization. With feedback from faculty and your peers, build a personalized “return-to-work” action plan and return to your role ready to apply new learning.  

Who Should Attend?

This program is intended for decision-makers in any size of company. Participants are curious, forward-thinking leaders seeking to expand their own capabilities and equip their organizations with modern processes and architecture. Senior executives already have a unique understanding of evidence-based decision making this content unlocks a new toolkit of data-based evidence and AI solutions. Managing with Data is designed for executives from a wide range of industries, functional backgrounds and geographies, who may not necessarily have a background in data sciences.

Program Faculty